Ship target recognition and classification based on genetic algorithm optimization of support vector machine
In order to realize effective maritime supervision and response,improve ship supervision efficiency and re-duce labor cost,the ship target recognition and classification method of genetic algorithm optimization support vector ma-chine is studied.Taking HU moment as the characteristic descriptor of ship target,the characteristic moment of ship target with rotation,scale and translation invariance is extracted from ship target image.The penalty factor and kernel parameters of SVM are optimized by genetic algorithm.In the support vector machine after parameter optimization,the characteristic moment samples of ship target are input and the recognition and classification results of ship target are output.Experimental results show that this method can extract the characteristic moments of ship target effectively.After parameter optimization,support vector machine can effectively reduce the computational complexity,speed up the detection target recognition and classification efficiency,and has better ship target recognition and classification performance.This method can accurately identify and classify ship targets.
genetic algorithmsupport vector machineship targetidentification and classificationHU mo-mentfeature descriptor
万方数据
维普
